基于WT-CNN-LSTM的溶解氧含量预测模型

溶解氧（Dissolved oxygen, DO）含量是影响水产养殖产量的重要因素之一，具有时序性、不稳定性和非线性等特点，且其影响因子过多、存在复杂的耦合关系，难以实现精准预测。针对传统长短时记忆神经网络（Long short term memory, LSTM）预测模型易引入冗余数据，且在训练过长序列时会出现梯度消失现象，从而不能捕捉因子间长期的依赖性问题，提出了基于小波变换（Wavelet transform, WT）、卷积神经网络（Convolutional neural network, CNN）和LSTM的溶解氧含量预测模型。首先，使用WT降低数据噪声；然后，使用CNN深度挖掘各变量之间的潜在关系；最后，利用LSTM的时序性预测2h后的水产养殖溶解氧含量。结果表明，本文提出的WT-CNN-LSTM模型预测效果良好，其平均绝对误差、均方根误差和决定系数分别为0.138、0.229和0.954，比传统LSTM模型分别优化了28.87%、21.03%和4.61%。     

龙须菜细胞壁多糖对硼的吸附性能研究

为研究龙须菜(Gracilaria lemaneiformis)细胞壁多糖对硼的吸附作用机制及官能团之间的交互作用,本试验分别采用电感耦合等离子发射光谱(ICP-OES)和傅里叶变换红外光谱(FTIR)技术对其细胞壁多糖组分在吸附试验中进行硼的测定和表征。结果表明,细胞壁去琼胶后,硼吸附量减少50.13%,半纤维素去除后,硼吸附量减少21.20%,故可得纤维素吸附量占细胞壁总硼吸附量的28.67%。同时,通过细胞壁不同组分脱硼及硼胁迫后的红外光谱表征结果可知,龙须菜细胞壁及多糖在吸附硼的过程中,羟基、羧基、多糖碳链C-C为硼离子的主要结合位点,其中,琼胶、半纤维素中起主要作用的官能团为羟基、羧基,纤维素中起主要作用的官能团为多糖碳链C-C。本研究结果为进一步探究龙须菜多糖组分与硼的内在结合机制提供了基础依据。     

扁杆藨草持续危害对棉花农艺和经济性状的影响

【目的】研究扁杆藨草持续危害对棉花的影响,为棉田该杂草科学防治提供依据。【方法】扁杆藨草种群密度设为60 株/m² ,测定其持续危害0、10、20、30、40、50 、60 d和全生育期棉花株高、茎粗、主茎节数、结铃数、单铃重、产量和纤维品质指标。【结果】棉花株高和茎粗随扁杆藨草危害持续期延长而减小。扁杆藨草持续危害期小于30 d,对棉花主茎节数和果枝数影响不显著,大于30 d则显著减少。扁杆藨草持续危害期对棉花中部和下部果枝结铃数影响不显著,显著引起上部果枝结铃数、单铃重减少。扁杆藨草持续危害期大于10 d,可使棉花产量显著减少,导致棉纤维品质指标下降。【结论】依据棉花产量指标,扁杆藨草防除应不晚于棉花打顶前30 d。     

Using vibrational molecular spectroscopy to detect moist heating induced carbohydrates structure changes in cool-climate adapted barley grain

There is limited research to study how moist heating affects internal structure of barley grain on a molecular basis. The objectives of this study were to use vibrational molecular spectroscopy: 1) to determine the moist heating induced changes of barley carbohydrate (CHO) structure on a molecular basis, 2) to study the effects of moist heating on CHO chemical profiles, Cornell Net Carbohydrate and Protein System (CNCPS) subfractions, in situ rumen degradation, and predicted intestinal carbohydrate supply of barley grain; and 3) to reveal the association between molecular structure spectral features and CHO related metabolic characteristics. Barley samples (CDC cowboy) were collected from Kernen Crop Research Farm (Saskatoon, Canada) during two consecutive years. Half of each sample was kept as raw barley and the other half underwent moist heating (autoclaving at 120 °C for 60 min). The molecular spectroscopy (attenuated total reflectance-fourier transform infrared, ATR-FTIR) was used to detect the barley CHO related molecular structure spectral features. Moist heating did not affect carbohydrate related chemical profiles and CNCPS subfractions but it decreased rumen degradable carbohydrate. Rumen undegradable and intestinal digestion of CHO subfractions were not affected by moist heating. The advanced vibrational molecular spectroscopy can be used to detect carbohydrate molecular spectral features. Nutrient utilization prediction using molecular spectral characteristics is warranted and further investigation is encouraged.     

酸催化下苯酚液化木材的制备与表征

在硫酸作用下用苯酚对人工林杨木和杉木进行液化,考察反应时间、反应温度等对液化反应的影响,并对液化产物进行表征分析.结果表明:1)在硫酸催化下,杨木和杉木被苯酚液化的历程相似,但残渣含量稍有不同.酸性催化剂不仅对纤维素和半纤维素起作用,对木质素也起作用.2)反应温度比反应时间对液化效率的影响大,二者均能影响液化产物的分子量和分子量分布.通常杉木液化产物的重均分子量高于杨木.3)液化过程中,木质素和半纤维素首先被液化,最后是纤维素.木材组分的分解、酚化和再缩聚反应主宰整个液化动力学过程及液化产物的结构特征.     

醋酸水溶液处理对杉树材影响

为了研究醋酸水溶液处理给杉树材重量带来的变化,使用醋酸水溶液对杉树材进行了处理。结果发现处理后杉树材重量的减小量大约等于抽出物的重量,而且随着醋酸水溶液浓度的增加而增加。利用傅立叶变换红外光谱法对处理后的杉树材及抽出物进行了光谱分析。从处理后杉树材的光谱图可以观察到3400cm-1附近的OH伸缩振动及1510cm-1附近的木质素中苯环C=C伸缩振动的吸收强度有增加倾向。从醋酸水溶液抽出物光谱图可以发现用浓度30%醋酸水溶液处理时木质素被溶出。图2表2参6。     

Prediction of bending properties for structural glulam using optimized distributions of knot characteristics and laminar MOE

This study established a prediction model for bending properties of glued-laminated timber (glulam) using optimized knot and modulus of elasticity (MOE) distributions of lumber laminate as the main input variables. For this purpose, knot and MOE data were investigated for all pieces of lumber that were prepared for glulam manufacturing, and statistical distributions of knot size, knot number in one lumber, and MOE of each laminate were optimized as distribution functions. These knot and MOE data were used as input variables in the prediction model for bending properties, and were also used in generating virtual glulam using the inverse transform method. Prediction of bending properties for glulam was carried out using the transformed section method, which is partially provided in ASTM D 3737 (Annex A4). Predicted values were compared with those from full-scale four-point bending tests for 60 six-layered glulams with 10 different laminar combinations. Finally, the allowable bending properties of glulam for each specific laminate combination were determined by calculating the fifth percentile of the modulus of rupture and the average modulus of elasticity from virtual test results of more than 1000 virtual glulams. From the results of this study, predicted bending properties for glulam and their distributions could be used for structural design in both allowable stress design and limit state design.     

基于机器视觉的温室番茄裂果检测

该文通过对温室番茄果实进行定位及裂果检测,可为番茄裂果率预估及后续裂果自动筛选提供参考。针对自然光照下采集的各类番茄图像,在相关颜色空间中进行阈值预分割,利用前期支持向量机训练得到的纹理特征分类器对预分割区域进行二次判别;之后在前景区域利用显著性角点分割构造边缘轮廓集,利用基于最小二乘法修正的改进霍夫变换拟合单个番茄目标;最后利用二维Gabor小波算子对拟合的单个番茄区域进行纹理特征提取及裂果判别。文中共采集82幅番茄图像,其中50幅图像作为训练集图像,32幅图像作为验证集,所提算法对测试集中总共128个番茄的果实正确检出率为91.41%,对其中35裂果的正确判别率为97.14%,裂果判别部分平均耗时21 ms。试验结果表明,该方法具有较好的鲁棒性与可靠性,对成熟期番茄裂果率的估计研究及采摘过程中裂果的自动分级筛选具有较好的指导意义,为未来实现温室番茄果实生长状态在线监测提供参考。     

一种大规模体数据压缩体绘制策略

针对基于GPU的大规模体数据直接体绘制过程中遇到的显存不足的问题，提出了一种大规模体数据的压缩绘制策略.该策略结合小波变换和分类矢量量化进行数据压缩，采用基于GPU的光线投射算法进行绘制，在绘制时，只解压变换当前绘制所需要的极少数数据，并结合多分辨率绘制，实现实时交互.基于CUDA的实验表明：该压缩绘制策略有效解决了显存不足问题，并且在保证交互绘制帧率的前提下获得了较好的成像质量.     

不同合成树脂工艺对改性材性能影响研究

为研究树脂对改性材性能的影响，采用2种不同工艺合成三聚氰胺-脲醛树脂（MUF），测试了树脂的相关性能。结果表明，不同合成工艺路线下制备的 MUF 树脂在固体含量、粘度、固化时间、游离甲醛含量间存在显著差异。最终树脂的分子结构类型相似性极高，但相同结构组分在不同树脂中所占比例各有差异。羟甲基基团在MUF2中所占比例高，而亚甲基桥键及醚键在MUF1中含量高。MUF1改性材的增重率（weight percent gain，WPG）值更大，但MUF2改性材的抗溶胀性（anti-swelling efficiency，ASE）和体积膨胀率（bulking rates，B）更高，MUF2改性材的尺寸稳定性更好。